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The ICANNGA series of Conferences has been organised since 1993 and
has a long history of promoting the principles and understanding of
computational intelligence paradigms within the scientific
community and is a reference for established workers in this area.
Starting in Innsbruck, in Austria (1993), then to Ales in Prance
(1995), Norwich in England (1997), Portoroz in Slovenia (1999),
Prague in the Czech Republic (2001) and finally Roanne, in France
(2003), the ICANNGA series has established itself for experienced
workers in the field. The series has also been of value to young
researchers wishing both to extend their knowledge and experience
and also to meet internationally renowned experts. The 2005
Conference, the seventh in the ICANNGA series, will take place at
the University of Coimbra in Portugal, drawing on the experience of
previous events, and following the same general model, combining
technical sessions, including plenary lectures by renowned
scientists, with tutorials.
From the contents: Neural networks - theory and applications: NNs
(= neural networks) classifier on continuous data domains- quantum
associative memory - a new class of neuron-like discrete filters to
image processing - modular NNs for improving generalisation
properties - presynaptic inhibition modelling for image processing
application - NN recognition system for a curvature primal sketch -
NN based nonlinear temporal-spatial noise rejection system -
relaxation rate for improving Hopfield network - Oja's NN and
influence of the learning gain on its dynamics Genetic algorithms -
theory and applications: transposition: a biological-inspired
mechanism to use with GAs (= genetic algorithms) - GA for decision
tree induction - optimising decision classifications using GAs -
scheduling tasks with intertask communication onto multiprocessors
by GAs - design of robust networks with GA - effect of degenerate
coding on GAs - multiple traffic signal control using a GA -
evolving musical harmonisation - niched-penalty approach for
constraint handling in GAs - GA with dynamic population size - GA
with dynamic niche clustering for multimodal function optimisation
Soft computing and uncertainty: self-adaptation of evolutionary
constructed decision trees by information spreading - evolutionary
programming of near optimal NNs
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